Put the title of your vignette here
Basic use of brainconn()
The brainconn() function allows users to input a binary/weighted and directed/directed (i.e. symmetric) connectivity matrix which can be plotted in MNI space onto several brain atlases provided with the package. The layout of the nodes and edges is created using ggraph, which does most of the heavy lifting here. The background is a custom_annotation using ggplot2.
The minimum user input requirements for the brainconn() function is a connectivity matrix. This can be read into r as a matrix or data.fame. Some example connectivity matrices can be found in the data/example folder. The number of rows/columns should match the number of regions in the selected atlas. The atlases currently included with in the package are:
Custom atlases can be added easily in .csv format (see adding custom atlas section).
By default, the view is a top view, the node.color is by network.
library(brainconn)
x <- read.csv("/Users/sidchopra/Dropbox/Sid/R_files/brainconn/data/example/example_unweighted_undirected.txt", header = F)
#setwd("~/Dropbox/Sid/R_files/brainconn")
brainconn(atlas ="Stages_melbBrain", conmat=x, node.size = 6)
You can change the default view, node, edge and background properties as well as show all nodes of the atlas, rather than just the ones that have connected edges.
brainconn(atlas ="Stages_melbBrain", conmat=x, view="left", node.size = 3, node.color = "hotpink", edge.width = 3, edge.color="darkblue", edge.alpha = 0.8, all.nodes = T, show.legend = F)
If the connectivity matrix (conmat) you input is not a binary matrix, i.e. the values are weighted, by default ggconn() will modulate the edge.width by the weighted values. scale.edge.width can be used to scale the edge width.
x <- read.csv("/Users/sidchopra/Dropbox/Sid/R_files/brainconn/data/example/example_weighted_undirected.txt", header = F)
brainconn(atlas ="schafer300_n7", conmat=x, node.size = 7,view="bottom", scale.edge.width = c(1,6), background.alpha = 0.4, show.legend = F)
You can also change the edge color by weight using the edge.color.weighted option.
x <- read.csv("/Users/sidchopra/Dropbox/Sid/R_files/brainconn/data/example/example_weighted_undirected.txt", header = F)
brainconn(atlas ="schafer300_n7", conmat=x, node.size = 7,view="bottom", edge.width = 2, edge.color.weighted = T, show.legend = T)
If a directed matrix (i.e. non symmetrical) is the input, the edges will be displayed as directed arrows, with the edge.width and edge.color serving the same purpose.:
x <- read.csv("/Users/sidchopra/Dropbox/Sid/R_files/brainconn/data/example/example_unweighted_directed.txt", header = F)
brainconn(atlas ="schafer300_n7", conmat=x, node.size = 4, view="right", edge.alpha = 0.4)
Weighted and directed matrix example:
x <- read.csv("/Users/sidchopra/Dropbox/Sid/R_files/brainconn/data/example/example_weighted_directed.txt", header = F)
brainconn(atlas ="schafer300_n7", conmat=x, view="front", edge.color.weighted=T)
You can auto add labels, but this doesn’t work to great if theirs a large number of edges.
x <- read.csv("/Users/sidchopra/Dropbox/Sid/R_files/brainconn/data/example/example_unweighted_undirected.txt", header = F)
brainconn(atlas ="Stages_melbBrain", conmat=x, labels = T, label.size = 2)
If you want to weight the nodes by a feature such as degree, you can provide a vector the length of the number of ROIs in the parcellation to node.size.
x_igraph <- igraph::graph_from_adjacency_matrix(as.matrix(x)) #convert connectivity matrix into an graph object.
d <- igraph::degree(x_igraph) #use igraph::degree to obtain a vector of nodal degree
d <- d[d != 0] #remove nodes with no edges
brainconn(atlas ="Stages_melbBrain", conmat=x, node.size = d)
Basic use of ggconn3D()
Currently, ggconn3D() is only able to visualize binary undirected connectivity matrices.
p <- brainconn3D(atlas ="Stages_melbBrain", conmat=x, show.legend = F)
p